Risk of Out-of-Hospital Cardiac Arrest in Aged Individuals in Relation to Cold Ambient Temperature - A Report From North Tochigi Experience

Impact of Extreme Temperature and Particulate Matter 2.5 on Outcomes of Out-of-Hospital Cardiac Arrest

BACKGROUND

Extreme temperature and particulate matter-2.5 (PM2.5) are known to affect the outcomes of out-of-hospital cardiac arrest (OHCA). However, studies that examine their effects at the exact time of OHCA occurrence are limited.

OBJECTIVE

This study aimed to investigate the impact of extreme cold, extreme heat, and PM2.5 on OHCA outcomes at the time of occurrence.

METHODS

We analyzed data from 82,497 OHCAs (aged > 18 years) in South Korea between January 2016 and December 2021. Extreme temperatures were defined as extreme cold (≤5th percentile) and extreme heat (≥95th percentile). PM2.5 refers to particulate matter ≤ 2.5 micrometers, with extreme PM2.5 defined as ≥95th percentile. The outcomes were survival to discharge and good neurological outcome, defined as a cerebral performance category of 1 or 2 at hospital discharge. We performed a multivariable logistic regression analysis to assess the impact of extreme temperature and PM2.5 on OHCA outcomes.

RESULTS

Extreme cold (-4.2°C to -20.2°C) showed no association with OHCA outcomes when compared to normal conditions (-0.9°C to 26.6°C). However, OHCAs during extreme heat (28.7°C to 39.3°C) showed a 15% significantly lower probability of survival to discharge (adjusted odds ratio [aOR]: 0.85, 95% confidence interval (CI): 0.74-0.98) compared to normal conditions. OHCAs during extreme PM2.5 (56 to 218 µg/m³) were associated with 14% lower probability of survival to discharge (aOR: 0.86, 95% CI: 0.75-0.99) compared to normal PM2.5 (0 to 43 µg/m³).

CONCLUSION

Extreme heat and PM2.5 were significantly associated with a decreased probability of survival to discharge in OHCA patients.

Short-term exposures to temperature and risk of sudden cardiac death in women: A case-crossover analysis in the Nurses' Health Study

Background

Sudden cardiac death (SCD) is a major source of mortality and is the first manifestation of heart disease for most cases. Thus, there is a definite need to identify risk factors for SCD that can be modified on the population level. Short-term exposures to temperature have been implicated as a potential risk factor. Our objective was to determine if short-term temperature exposures were associated with increased risk of SCD in a US-based time-stratified case-crossover study.

Methods

A total of 465 cases of SCD were identified among participants of the prospective Nurses' Health Study (NHS). Control days were selected from all other matching days of the week within the same month as the case day. Average ambient temperature on the current day (Lag0) and preceding 27 days (Lags1-27) was determined at the residence level using 800-m resolution estimates. Conditional logistic distributed lag nonlinear models (DLNMs) were used to assess the relative risk (RR) of the full range of temperature exposures over the lag period.

Results

Warmer exposures in the days before event and colder temperatures 21-28 days prior were associated with increased risks of SCD. These results were driven by associations in regions other than the Northeast and among married women.

Conclusions

Both warm and cold ambient temperatures are suggestively associated with risks of SCD among middle-aged and older women living across the United States.

Seasonal Variation in the Incidence of In-Hospital Cardiac Arrest

BACKGROUND

Seasonal variation in cardiovascular outcomes, including out-of-hospital cardiac arrest, has been described.

OBJECTIVES

This study aimed to investigate seasonal differences in the incidence of in-hospital cardiac arrest (IHCA) and associated mortality.

METHODS

Using National Inpatient Sample data from 2005 to 2019, we determined the incidence of IHCA in 4 seasons. The primary objective was to evaluate overall seasonal trends in the incidence of IHCA and trends stratified by sex, age, and region. The secondary aim was to determine common causes of admission that led to IHCA, differences in those with shockable vs nonshockable IHCA, independent predictors of IHCA, and seasonal variation in IHCA-related in-hospital mortality and length of stay.

RESULTS

A consistent winter peak was observed in the incidence of IHCA in both male and female patients over the years in all age groups except young (<45 years) and in all regions. In 2019, both unadjusted and risk-adjusted odds of IHCA were higher (OR: 1.13; P < 0.001; adjusted OR: 1.08; P = 0.033) in winter than in summer. Patients with shockable IHCA were mainly admitted for cardiac and those with nonshockable IHCA for noncardiac conditions. No seasonal variation was observed in in-hospital mortality after IHCA. Therefore, seasonal variation exists, with a higher IHCA event rate in winter than summer.

CONCLUSIONS

Improving insights into factors that influence the higher IHCA event rate during winter may help with proper resource allocation, development of strategies for early recognition of patients vulnerable to IHCA, and closer monitoring and optimization of care to prevent IHCA and improve outcomes.

Effect of Temperature on Emergency Ambulance Call-Outs for Cardiovascular Causes: A Scoping Review

Climate change has increased interest in the effects of the thermal environment on cardiovascular health. Most studies have focused on mortality data. However, pre-hospital care data are better able to evaluate these effects, as they can register the full spectrum of the disease in real time. This scoping review aims to synthesize the epidemiological evidence regarding the effects of the thermal environment on cardiovascular morbidity in the pre-hospital setting, evaluated through ambulance calls. A staged literature search was performed using the PubMed database for the period between 1st January 2000 and 30th March 2023, using the MeSH terms "Weather" AND "Emergency Medical Services". A total of 987 publications were identified that examined the correlation between the thermal environment and ambulance call-outs for cardiovascular causes. The studies were mostly ecological time series, with significant variability in the methodological aspects employed. An increase in the number of ambulance call-outs has been observed in association with low temperatures, both for overall cardiovascular pathologies and for certain pathological subtypes. For high temperatures, no effect has been observed in overall call-outs, although an increase has been observed during heat waves. The demand for ambulances for cardiac arrests is increased by both low and high temperatures and during heat waves. Ambulance call-outs for cardiovascular causes increase with low temperatures and heat waves, with no significant increase in the overall demand associated with high temperatures. Ambulance call-outs for cardiac arrests are the only subtype that is increased by high temperatures.

Machine learning algorithms for predicting days of high incidence for out-of-hospital cardiac arrest

Predicting out-of-hospital cardiac arrest (OHCA) events might improve outcomes of OHCA patients. We hypothesized that machine learning algorithms using meteorological information would predict OHCA incidences. We used the Japanese population-based repository database of OHCA and weather information. The Tokyo data (2005-2012) was used as the training cohort and datasets of the top six populated prefectures (2013-2015) as the test. Eight various algorithms were evaluated to predict the high-incidence OHCA days, defined as the daily events exceeding 75% tile of our dataset, using meteorological and chronological values: temperature, humidity, air pressure, months, days, national holidays, the day before the holidays, the day after the holidays, and New Year's holidays. Additionally, we evaluated the contribution of each feature by Shapley Additive exPlanations (SHAP) values. The training cohort included 96,597 OHCA patients. The eXtreme Gradient Boosting (XGBoost) had the highest area under the receiver operating curve (AUROC) of 0.906 (95% confidence interval; 0.868-0.944). In the test cohorts, the XGBoost algorithms also had high AUROC (0.862-0.923). The SHAP values indicated that the "mean temperature on the previous day" impacted the most on the model. Algorithms using machine learning with meteorological and chronological information could predict OHCA events accurately.

Effects of temperature and humidity on acute myocardial infarction hospitalization in a super-aging society

Weather conditions affect the incidence of acute myocardial infarction (AMI). However, little is known on the association of weather temperature and humidity with AMI hospitalizations in a super-aging society. This study sought to examine this association. We included 87,911 consecutive patients with AMI admitted to Japanese acute-care hospitals between April 1, 2012 and March 31, 2015. The primary outcome was the number of AMI hospitalizations per day. Multilevel mixed-effects linear regression models were used to estimate the association of the average temperature and humidity, 1 day before hospital admission, with AMI hospitalizations, after adjusting for weather, hospital, and patient demographics.Lower temperature and humidity were associated with an increased number of AMI hospitalizations (coefficient − 0.500 [− 0.524 to − 0.474] per °C change, p < 0.001 and coefficient − 0.012 [− 0.023 to − 0.001] per % change, p = 0.039, respectively). The effects of temperature and humidity on AMI hospitalization did not differ by age and sex (all interaction p > 0.05), but differed by season. However, higher temperatures in spring (coefficient 0.089 [0.025 to 0.152] per °C change, p = 0.010) and higher humidity in autumn (coefficient 0.144 [0.121 to 0.166] per % change, p < 0.001) were risk factors for AMI hospitalization. Increased average temperatures and humidity, 1 day before hospitalization, are associated with a decreased number of AMI hospitalizations.

Extreme temperature and out-of-hospital-cardiac-arrest. Nationwide study in a hot climate country

BACKGROUND

Out-of-hospital-cardiac arrest (OHCA) is frequently linked to environmental exposures. Climate change and global warming phenomenon have been found related to cardiovascular morbidity, however there is no agreement on their impact on OHCA occurrence. In this nationwide analysis, we aimed to assess the incidence of the OHCA events attended by emergency medical services (EMS), in relation to meteorological conditions: temperature, humidity, heat index and solar radiation.

METHODS

We analyzed all adult cases of OHCA in Israel attended by EMS during 2016-2017. In the case-crossover design, we compared ambient exposure within 72 h prior to the OHCA event with exposure prior to the four control times using conditional logistic regression in a lag-distributed non-linear model.

RESULTS

There were 12,401 OHCA cases (68.3% were pronounced dead-on-scene). The patients were on average 75.5 ± 16.2 years old and 55.8% of them were males. Exposure to 90th and 10th percentile of temperature adjusted to humidity were positively associated with the OHCA with borderline significance (Odds Ratio (OR) =1.20, 95%CI 0.97; 1.49 and OR 1.16, 95%CI 0.95; 1.41, respectively). Relative humidity below the 10th percentile was a risk factor for OHCA, independent of temperature, with borderline significance (OR = 1.16, 95%CI 0.96; 1.38). Analysis stratified by seasons revealed an adverse effect of exposure to 90th percentile of temperature when estimated in summer (OR = 3.34, 95%CI 1.90; 3.5.86) and exposure to temperatures below 10th percentile in winter (OR = 1.75, 95%CI 1.23; 2.49). Low temperatures during a warm season and high temperatures during a cold season had a protective effect on OHCA. The heat index followed a similar pattern, where an adverse effect was demonstrated for extreme levels of exposure.

CONCLUSIONS

Evolving climate conditions characterized by excessive heat and low humidity represent risk factors for OHCA. As these conditions are easily avoided, by air conditioning and behavioral restrictions, necessary prevention measures are warranted.